KuaiLive is the first publicly released real-time interactive dataset for live streaming recommendation, with logs from 23,772 users and 452,621 streamers over 21 days plus timestamps, multi-type interactions, and side features.
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CS3 strengthens two-tower retrievers via cycle-adaptive feature denoising, cross-tower mutual awareness, and cascade knowledge reuse, delivering consistent gains on public datasets and up to 8.36% revenue lift in production advertising at millisecond latency.
SSRLive combines generative and discriminative modules with dynamic semantic IDs to improve live streaming recommendations, reporting gains of +3.38% watch time, +0.72% GMV, +3.12% follower growth, and +2.92% interaction volume in online A/B tests.
citing papers explorer
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KuaiLive: A Real-time Interactive Dataset for Live Streaming Recommendation
KuaiLive is the first publicly released real-time interactive dataset for live streaming recommendation, with logs from 23,772 users and 452,621 streamers over 21 days plus timestamps, multi-type interactions, and side features.
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CS3: Efficient Online Capability Synergy for Two-Tower Recommendation
CS3 strengthens two-tower retrievers via cycle-adaptive feature denoising, cross-tower mutual awareness, and cascade knowledge reuse, delivering consistent gains on public datasets and up to 8.36% revenue lift in production advertising at millisecond latency.
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SSRLive: Live Streaming Recommendation with Dynamic Semantic ID
SSRLive combines generative and discriminative modules with dynamic semantic IDs to improve live streaming recommendations, reporting gains of +3.38% watch time, +0.72% GMV, +3.12% follower growth, and +2.92% interaction volume in online A/B tests.